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Responses of European anchovy vital rates and population growth to environmental fluctuations: An individual-based modeling approach

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  • Pethybridge, H.
  • Roos, D.
  • Loizeau, V.
  • Pecquerie, L.
  • Bacher, C.

Abstract

A size-structured, bioenergetics model was implemented to examine the effects of short-term environmental changes on European anchovy, Engraulis encrasicolus, in the North-western Mediterranean Sea. The model approach was based on Dynamic Energy Budget (DEB) theory and details the acquisition and allocation of energy (Jd−1) during an organisms’ full life-cycle. Model calibration was achieved using biometric data collected from the Gulf of Lions between 2002 and 2011. Bioenergetics simulations successfully captured ontogenetic and seasonal growth patterns, including active growth in spring/summer, loss of mass in autumn/winter and the timing and amplitude of multi-batch spawning events. Scenario analysis determined that vital rates (growth and fecundity) were highly sensitive to short-term environmental changes. The DEB model provided a robust foundation for the implementation of an individual-based population model (IBM) in which we used to test the responses of intrinsic and density-independent population growth rates (r) to observed and projected environmental variability. IBM projections estimate that r could be reduced by as much as 15% (relative to that estimated under mean conditions) due to either a 5% (0.8°C) drop in temperature (due to a reduced spawning duration), a 18% (25mg zooplanktonm−3) depletion in food supply, a 30% increase in egg mortality rates, or with the phytoplankton bloom peaking 5 weeks earlier (in late-February/Winter). The sensitivity of r to short-term (1 year) and long-term (4–10 year) environmental changes were similar, highlighting the importance of first-year spawners. In its current form, the models presented here could be incorporated into spatially-explicit, higher-trophic (predator–prey and end-to-end ecosystem), larval-dispersal and toxicokinetic models or adapted to other short-lived foraging fish (clupeid) species.

Suggested Citation

  • Pethybridge, H. & Roos, D. & Loizeau, V. & Pecquerie, L. & Bacher, C., 2013. "Responses of European anchovy vital rates and population growth to environmental fluctuations: An individual-based modeling approach," Ecological Modelling, Elsevier, vol. 250(C), pages 370-383.
  • Handle: RePEc:eee:ecomod:v:250:y:2013:i:c:p:370-383
    DOI: 10.1016/j.ecolmodel.2012.11.017
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    1. Megrey, Bernard A. & Rose, Kenneth A. & Klumb, Robert A. & Hay, Douglas E. & Werner, Francisco E. & Eslinger, David L. & Smith, S. Lan, 2007. "A bioenergetics-based population dynamics model of Pacific herring (Clupea harengus pallasi) coupled to a lower trophic level nutrient–phytoplankton–zooplankton model: Description, calibration, and se," Ecological Modelling, Elsevier, vol. 202(1), pages 144-164.
    2. Paloma Martín & Ana Sabatés & Josep Lloret & Javier Martin-Vide, 2012. "Climate modulation of fish populations: the role of the Western Mediterranean Oscillation (WeMO) in sardine (Sardina pilchardus) and anchovy (Engraulis encrasicolus) production in the north-western Me," Climatic Change, Springer, vol. 110(3), pages 925-939, February.
    3. Ospina-Alvarez, Andrés & Parada, Carolina & Palomera, Isabel, 2012. "Vertical migration effects on the dispersion and recruitment of European anchovy larvae: From spawning to nursery areas," Ecological Modelling, Elsevier, vol. 231(C), pages 65-79.
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    2. Boyd, Robin & Roy, Shovonlal & Sibly, Richard & Thorpe, Robert & Hyder, Kieran, 2018. "A general approach to incorporating spatial and temporal variation in individual-based models of fish populations with application to Atlantic mackerel," Ecological Modelling, Elsevier, vol. 382(C), pages 9-17.
    3. Dambrine, Chloé & Huret, Martin & Woillez, Mathieu & Pecquerie, Laure & Allal, François & Servili, Arianna & de Pontual, Hélène, 2020. "Contribution of a bioenergetics model to investigate the growth and survival of European seabass in the Bay of Biscay – English Channel area," Ecological Modelling, Elsevier, vol. 423(C).
    4. Athanasios Gkanasos & Stylianos Somarakis & Kostas Tsiaras & Dimitrios Kleftogiannis & Marianna Giannoulaki & Eudoxia Schismenou & Sarantis Sofianos & George Triantafyllou, 2019. "Development, application and evaluation of a 1-D full life cycle anchovy and sardine model for the North Aegean Sea (Eastern Mediterranean)," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-24, August.
    5. Desforges, Jean-Pierre & Marques, Gonçalo M. & Beumer, Larissa T. & Chimienti, Marianna & Blake, John & Rowell, Janice E. & Adamczewski, Jan & Schmidt, Niels Martin & van Beest, Floris M., 2019. "Quantification of the full lifecycle bioenergetics of a large mammal in the high Arctic," Ecological Modelling, Elsevier, vol. 401(C), pages 27-39.
    6. Gatti, Paul & Petitgas, Pierre & Huret, Martin, 2017. "Comparing biological traits of anchovy and sardine in the Bay of Biscay: A modelling approach with the Dynamic Energy Budget," Ecological Modelling, Elsevier, vol. 348(C), pages 93-109.
    7. Chimienti, Marianna & Desforges, Jean-Pierre & Beumer, Larissa T. & Nabe-Nielsen, Jacob & van Beest, Floris M. & Schmidt, Niels Martin, 2020. "Energetics as common currency for integrating high resolution activity patterns into dynamic energy budget-individual based models," Ecological Modelling, Elsevier, vol. 434(C).
    8. Dortel, E. & Pecquerie, L. & Chassot, E., 2020. "A Dynamic Energy Budget simulation approach to investigate the eco-physiological factors behind the two-stanza growth of yellowfin tuna (Thunnus albacares)," Ecological Modelling, Elsevier, vol. 437(C).

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